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558 results for “VR”

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zenodo36/100

VR Experiences with wolves - SPSS-Output

<p>The file is the SPSS-Output for the publication &quot;Virtual Reality Nature Experiences Involving Wolves in YouTube: Presence, Emotion, and Attitudes in Immersive and Non-Immersive Settings&quot; - Sustainability</p>

opencc-by-4.0Mar 2020View details →
zenodo36/100

Vr-Together pilot 3: Sound and SFX

<p>VR-Together Pilot 3 sound files and SFX</p> <p>Sound files and SFX for the&nbsp;<a href="https://vrtogether.eu/about-vr-together/pilots/pilot3/">Pilot 3 of the VR-Together project</a>.</p> <ul> <li>Number of files: 23</li> <li>Audio: Stereo, 44,1kHz</li> <li>Bits: 16</li> </ul> <p>VR-Together&nbsp;has been funded by the European Commission as part of the H2020 program, under the grant agreement 762111.</p>

opencc-by-4.0Nov 2020View details →
zenodo36/100

VR-Together pilot 3: Video Composition (scene 4)

<p>VR-Together Pilot 3 video composition: scene 4.</p> <p>Video composition of the fourth and last scene of&nbsp;the&nbsp;<a href="https://vrtogether.eu/about-vr-together/pilots/pilot3/">Pilot 3 of the VR-Together project</a>.</p> <ul> <li>Dimensions: 3840x2160</li> <li>Codec: Timecode, Linear PCM, H.264</li> <li>Duration: 01:20</li> <li>Audio: Stereo</li> </ul> <p>VR-Together&nbsp;has been funded by the European Commission as part of the H2020 program, under the grant agreement 762111.</p>

opencc-by-4.0Nov 2020View details →
zenodo36/100

VR-Together pilot 3: Video Composition (scene 1)

<p>VR-Together Pilot 3 video composition: scene 1.</p> <p>Video composition of the first scene of&nbsp;the&nbsp;<a href="https://vrtogether.eu/about-vr-together/pilots/pilot3/">Pilot 3 of the VR-Together project</a>.</p> <ul> <li>Dimensions: 3840x2160</li> <li>Codec: Timecode, Linear PCM, H.264</li> <li>Duration: 04:51</li> <li>Audio: Stereo</li> </ul> <p>VR-Together&nbsp;has been funded by the European Commission as part of the H2020 program, under the grant agreement 762111.</p>

opencc-by-4.0Nov 2020View details →
zenodo36/100

VR-Together pilot 3: Video Composition (scene 3)

<p>VR-Together Pilot 3 video composition: scene 3.</p> <p>Video composition of the third scene of&nbsp;the&nbsp;<a href="https://vrtogether.eu/about-vr-together/pilots/pilot3/">Pilot 3 of the VR-Together project</a>.</p> <ul> <li>Dimensions: 3840x2160</li> <li>Codec: Timecode, Linear PCM, H.264</li> <li>Duration: 01:49</li> <li>Audio: Stereo</li> </ul> <p>VR-Together&nbsp;has been funded by the European Commission as part of the H2020 program, under the grant agreement 762111.</p>

opencc-by-4.0Nov 2020View details →
zenodo36/100

VR Safety Amulet

This is a amulet (or a charm) with a wish for a safety in VR. (Like the one you can get from Japanese shrine.) * This amulet is not endorsed by any shrines, and is personal in nature. Source: Objaverse 1.0 / Sketchfab

opencc-byJan 2022View details →
zenodo36/100

Abbazia Valtolla - 3D-P - VR torre

Ricostruzione 3D del sito archeologico dell'Abbazia di Valtolla in comune di Morfasso (Piacenza). Esperienza immersiva attravero un visore VR da indossare, con centro nella torre Source: Objaverse 1.0 / Sketchfab

opencc-byJun 2022View details →
zenodo36/100

Croce in pietra (museo dei Cimbri, Lessinia, VR)

Croce in pietra a San Bortolo (Lessinia, Verona), anno 1852. Fotogrammetria da smartphone in alta qualità, circa 60 minuti di elaborazione. # English Stone crux in Verona (Italy) regional park of Lessinia, museum of the Cimbri (ancient tribe in Europe, Celtic and Germanic people): https://en.wikipedia.org/wiki/Cimbri. Year 1852. Photogrammetry from smartphone photos, high quality, about 60 minutes of processing. Source: Objaverse 1.0 / Sketchfab

opencc-byJun 2022View details →
zenodo36/100

Abbazia Valtolla - 3D-P - VR navata

Ricostruzione 3D del sito archeologico dell'Abbazia di Valtolla in comune di Morfasso (Piacenza). Esperienza immersiva attravero un visore VR da indossare, con centro nella navata Source: Objaverse 1.0 / Sketchfab

opencc-byJun 2022View details →
zenodo36/100

Stonehenge England - VR

Stonehenge is a prehistoric monument in Wiltshire, England, two miles (3 km) west of Amesbury. It consists of a ring of standing stones, with each standing stone around 13 feet (4.0 m) high, seven feet (2.1 m) wide and weighing around 25 tons. The stones are set within earthworks in the middle of the most dense complex of Neolithic and Bronze Age monuments in England, including several hundred burial mounds. One of the most famous landmarks in the United Kingdom, Stonehenge is regarded as a British cultural icon. It has been a legally protected Scheduled Ancient Monument since 1882 when legislation to protect historic monuments was first successfully introduced in Britain. The site and its surroundings were added to UNESCO's list of World Heritage Sites in 1986. Stonehenge is owned by the Crown and managed by English Heritage; the surrounding land is owned by the National Trust Source: Objaverse 1.0 / Sketchfab

opencc-byOct 2019View details →
zenodo36/100

Multitask Human Navigation in VR with Motion Tracking

<p>Data from human subjects in virtual reality performing some combination of collecting targets, avoiding obstacles, and following a path. Raw data has been parsed into 300 ms samples for use in machine learning algorithms. The data includes object positions in the virtual environment, human position tracking, and task instructions. </p> <p> </p>

opencc-by-4.0Jan 2017View details →
zenodo36/100

The Virtual Reality(VR) Enviroments used in the study

<p>These are the images of the positive, negative and neutral environments used in the&nbsp;</p><p>study of the correlation of gait with depression&nbsp;</p>

opencc-by-4.0Oct 2023View details →
zenodo36/100

The VR Documentary – History, Theory, Examples

<p>While VR has now almost become established on the games market for home use by several large commercial manufacturers of displays and content providers, the use in the educational context is not yet very large. This applies in particular to artistic projects that, like documentary film, want to combine public education and creative expression. But especially at festivals that take place regularly (such as the DOK Neuland section of the Leipzig Documentary Film Festival), there are spaces to present innovative non-fictional projects – and the demand is not small, there are usually even waiting lists for use. The lecture would like to approach this new form between creative practice, world building and interactive user integration in three parts: First, it will deal with the (recent) history of VR and ask about the essential factors in the implementation of current forms. Second, methods and theories are presented that emphasize the potential for innovation – also compared to linear documentary film or other digital forms like web docs – and I will outline the special nature of the form between experience, storytelling and participation. Third and lastly, of course, some examples should also be presented briefly, which have received a lot of encouragement from users and practitioners in recent years. These are selected in such a way that they describe as many different modalities of non-fictional VR as possible. Florian Mundhenke, PD Dr. phil. habil., since 2020 Associate Professor for Cultural and Media Studies (DAAD) at the Institute for Modern Languages and Cultural Studies at University of Alberta in Edmonton/Canada. From 2018-2020 Temporary Professor (W3) for Media Studies and Media Culture at University of Leipzig. Before he was Senior Lecturer at the Institute for Media and Communication (IMK) at University of Hamburg, Associate Professor for Media Hybridity ("Juniorprofessor für Mediale Hybride") at the University of Leipzig, and Research Assistant at University of Marburg. He was speaker of the DFG-funded research network "Cinema as an experience space": www.erfahrungsraum-kino.de. PhD dissertation on the phenomenon of chance in film in 2008 (Marburg: Schueren). Habilitation (Lecture qualification thesis) on hybrid forms between documentary and fictional film in 2016 (Wiesbaden: Springer VS). Fields of research include intersections of arts and media in history and practice (intermedial, transcultural), non-fictional media (documentary film, VR films, i-docs, AR), methods and concepts of Digital Humanities in media studies, theories of media genres and genre development, intersectional media theory (gender, race, class, ideology), and world cinema with a focus on the Far East (Japan, Korea, Taiwan).&nbsp;</p><p>Florian Mundhenke https://apps.ualberta.ca/directory/person/mundhenk&nbsp;</p><p>Email: mundhenk@ualberta.ca</p>

opencc-by-4.0Dec 2023View details →
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Online and offline VR motion sickness ratings and associated cognitive peformance

<p>This is the data associated with the manuscript "Reduced VR Motion Sickness by Applying Random-phase Transcranial Alternating Current Stimulation to the Left Parietal Cortex"</p>

opencc-by-4.0Dec 2023View details →
zenodo36/100

VR - Enniscorthy Carving Animated

Note: The VR aspect will only work with VR headsets or on a Mobile device with a VR app installed. The history of halberdier posed more questions than answers, and it was our intention to attempt to ascertain its origins, date, and best methods for conservation. Following initial analysis, it became obvious that the wall art has considerably more detail than originally thought e.g. buttons on its 'tunic', cheeks and a mouth, and hachured clothing. It is now obvious that he is more than a mural, his clothing is in fact engraved, and with some considerable skill, but again, further consideration will have to be given to comparing him to other sites both nationally and internationally. Dr. Sherlock's report is available to download [here](https://docreader.reciteme.com/doc/url?q=http://enniscorthycastle.ie/wp-content/uploads/2022/02/Enniscorthy-Castle-Report-2012-R-Sherlock.pdf). ![]() Source: Objaverse 1.0 / Sketchfab

opencc-byJul 2022View details →
zenodo36/100

Mannequin hand [Photogrammetry | VR Ready]

VR Ready photogrammetry hands, FBX hand from Oculus rig is used and skinned to match the model. Enjoy! Source: Objaverse 1.0 / Sketchfab

opencc-byApr 2021View details →
zenodo36/100

Quill VR Inktober 2019 # 23 - Ancient

The Sweat Lodge Ceremony Animated video here!: https://www.youtube.com/watch?v=CLsRiFnFBCE&amp;feature=youtu.be A lot of people are very skeptical about this (even I was...) so I thought I would share the ancient practice that still is used today throughout various indigenous groups across the world. Myself, a person not of this descent attended a few ceremonies and I felt truly welcomed and it was a really fascinating experience. The lodge is represented as the "mother's womb" and the most purest place to be healed (once you are born you are exposed to the world's pain and suffering) . In the lodge, you are closed off from the world and in complete darkness as if you are looking at the beginning of life. If felt kind of like an immersive meditation experience. There is a long explanation online but I highly recommend go trying for yourself. :) Thank you ! #3Dinktober2019 #3DInktober2019-Ancient Source: Objaverse 1.0 / Sketchfab

opencc-byOct 2019View details →
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Output files for Variable-Resolution Community Earth System Model (VR-CESM) simulations with highest resolutions over the Euro-Mediterranean

<p>Output files for Variable-Resolution Community Earth System Model (VR-CESM) simulations with highest resolutions over the Euro-Mediterranean and notebooks created for analyses and visualization.</p> <p>Configuration names:</p> <ul> <li>ne30_n</li> <li>ne30x4_n</li> <li>ne30x4_t</li> <li>ne30x8_t</li> </ul> <p>Variables at single level: PHIS,PRECC,PRECL,PS,TREFHT,LHFLX,SWCF,LWCF,TMQ,SNOWHLND</p> <p>Variables at pressure levels:U,V,OMEGA,RELHUM,Z3,Q</p>

opencc-by-4.0Nov 2024View details →
zenodo36/100

Artemis Mi amor la luna aria VR

<p>The visuals in this film were crafted by painting in Tilt Brush using the Oculus Quest headset, injected as 360-degree footage using the 360 VideoMetadataTool, and combined with the audio in Adobe Premiere Pro by Taana Rose. Autumn Ayre Aria 360 degree VR music video. Composer &amp; librettist: Taana Rose Performers: Operatic Mezzo Soprano: Luisa Tarnawski Operatic Tenor: Connor Willmore Pianist: Melfred Lijauco VR art and video: Taana Rose utilising Tilt Brush, and remixing Poly models. Libretto: Leaves are turning hearts burning, burning. The cold creeps in gives you pins and needles. Dusk turns to dawn, you are reborn, you are reborn. Once forlorn you are reborn, you are reborn. Winter has come, do not feel numb, you are full of life, you got through your strife. Ah ah ah. Come, do not feel numb, you are full of life, you got through your strife. Ah ah ah. Leaves are turning hearts are burning, burning. The cold crept in gave me pins and needles, I survived the hunt. At dawn, the forest is reborn, reborn. Once forlorn you are reborn, you are reborn. Winter has come, do not feel numb, you are full of life, you got through your strife.</p>

opencc-by-4.0Dec 2021View details →
zenodo36/100

CEAP-360VR: A Continuous Physiological and Behavioral Emotion Annotation Dataset for 360 VR Videos

<p><a href="http://ieeexplore.ieee.org/document/9599346">CEAP-360VR: A Continuous Physiological and Behavioral Emotion Annotation Dataset for 360&deg; Videos</a></p> <p><br> ## General Information<br> We develop the <a href="http://www.dis.cwi.nl/ceap-360vr-dataset/">CEAP-360VR</a> dataset&nbsp;to address the lack of continuously annotated behavioral and physiological datasets for 360 video VR affective computing. Accordingly, this dataset contains a) questionnaires (SSQ, IPQ, NASA-TLX); b) continuous valence-arousal annotations; c) head and eye movements as well as left and right eye pupil diameters while watching videos; d) peripheral physiological responses (ACC, EDA, SKT, BVP, HR, IBI). Our dataset also concludes the data pre-processing, data validating scripts, along with dataset description and key steps in the stage of data acquisition and pre-processing.</p> <p><br> ## Dataset Structure<br> The &nbsp;CEAP-360VR folder contains the following six subfolders</p> <p>1_Stimuli<br> 2_QuestionnaireData<br> 3_AnnotationData<br> 4_BehaviorData<br> 5_PhysioData<br> 6_Scripts<br> The following is a detailed description of each sub-file:</p> <p>1_Stimuli</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;- VideoThumbNails<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the eight thumbNails for each video (.jpg)<br> &nbsp;&nbsp;&nbsp;&nbsp;- VideoInfo.json<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the detailed information for eight videos</p> <p>2_QuestionnaireData</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;- PXX_Questionnaire_Data.json (X = 1, 2, ..., 32)<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains questionnaire data for each participant</p> <p>3_AnnotationData</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;- Raw<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the raw annotation data captured from the Joy-Con joystick for each participant<br> &nbsp;&nbsp;&nbsp;&nbsp;- Transformed<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the transformed valence-arousal data generated from the raw data for each participant<br> &nbsp;&nbsp;&nbsp;&nbsp;- Frame<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the re-sampled annotation data from the transformed data for each participant</p> <p>4_BehaviorData</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;- Raw<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the raw behavior data captured from the HTC VIVE Pro Eye Tobii Device for each participant<br> &nbsp;&nbsp;&nbsp;&nbsp;- Transformed<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the transformed heam/eye movement data (pitch/yaw) generated from the raw data, as well as pupil diameter data for each participant<br> &nbsp;&nbsp;&nbsp;&nbsp;- Frame<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the re-sampled behavior data generated from the transformed data for each participant<br> &nbsp;&nbsp;&nbsp;&nbsp;- HM_ScanPath<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the head scanpath data generated from the transformed data for each participant<br> &nbsp;&nbsp;&nbsp;&nbsp;- EM_Fixation<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the eye gaze fixation data generated from the transformed data for each participant</p> <p>5_PhysioData</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;- Raw<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the raw physiological data captured from the Empatica E4 wristband for each participant<br> &nbsp;&nbsp;&nbsp;&nbsp;- Transformed<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the transformed physiological data generated from the raw data for each participant<br> &nbsp;&nbsp;&nbsp;&nbsp;- Frame<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the re-sampled physiological data from the transformed data for each participant</p> <p>6_Scripts</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;- Unity Project<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains the complete project of our user-controlled experiment (Unity 2018.4.1f1, HTC VIVE Pro Eye HMD)<br> &nbsp;&nbsp;&nbsp;&nbsp;- Data Processed<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains scripts that undertake the pre-processing steps for converting the raw data to the transformed/frame data in the transformed and frame folders.<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;conatins scripts for continuous annotation, behavior and physiological data analysis and visualization.<br> &nbsp;&nbsp;&nbsp;&nbsp;- CEAP-360VR_Baseline<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains scripts to generate processed behavioral and physiological data with V-A labels for deep learning experiments and features for machine learning experiments.<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;contains scripts to run ML and DL experiments under both &nbsp;subject-dependent and subject-independent model.</p> <p><br> ## Dataset Description<br> The CEAP-360VR Dataset [Description.pdf](https://github.com/cwi-dis/CEAP-360VR-Dataset/blob/master/CEAP-Dataset%20Description.pdf) introduces the dataset description and key steps in the stage of data acquisition and pre-processing.</p> <p><br> ## Dataset License<br> CEAP-360VR dataset is licensed under a [Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license].</p> <p>## Citation</p> <p>Please cite our paper in any published work that uses this dataset as follows:<br> - Plain Text<br> T. Xue, A. El Ali, T. Zhang, G. Ding, and P. Cesar, &quot;CEAP-360VR: A Continuous Physiological and Behavioral Emotion Annotation Dataset for 360&deg; Videos,&quot; in IEEE Transactions on Multimedia, doi: 10.1109/TMM.2021.3124080.</p> <p>- BibTex<br> @ARTICLE{Xue2021CEAP-360VR,<br> &nbsp;&nbsp;author={Xue, Tong and Ali, Abdallah El and Zhang, Tianyi and Ding, Gangyi and Cesar, Pablo},<br> &nbsp;&nbsp;journal={IEEE Transactions on Multimedia},&nbsp;<br> &nbsp;&nbsp;title={CEAP-360VR: A Continuous Physiological and Behavioral Emotion Annotation Dataset for 360&deg; Videos},&nbsp;<br> &nbsp;&nbsp;year={2021},<br> &nbsp;&nbsp;volume={},<br> &nbsp;&nbsp;number={},<br> &nbsp;&nbsp;pages={1-1},<br> &nbsp;&nbsp;doi={https://doi.org/10.1109/TMM.2021.3124080}}</p> <p><br> ## Usage</p> <p>&nbsp;1. We have performed the time alignment of different types of data and&nbsp;<br> &nbsp;&nbsp;&nbsp;&nbsp;videos for each participant, as well as the proceesing scripts that&nbsp;<br> &nbsp;&nbsp;&nbsp;&nbsp;can be used to generate both the transformed and frame data. &nbsp;&nbsp;<br> &nbsp;&nbsp;&nbsp;&nbsp;Researchers can run their analysis methods on them.<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<br> &nbsp;2. For researchers who want to try other data processing methods, you can directly use the raw data.</p> <p><br> ## About&nbsp;<br> The CEAP-360VR Dataset is maintained by Key Laboratory of Digital Performance and Simulation Technology at Beijing Institute of Technology and the Distributed &amp; Interactive Systems (DIS) research group at Centrum Wiskunde &amp; Informatica .</p> <p>Contact the authors<br> - Tong Xue: xuetong@bit.edu.cn, xue.tong@cwi.nl<br> - Abdallah El Ali: abdallah.el.ali@cwi.nl</p>

opencc-by-4.0Nov 2021View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record